Kexin Pei became a Neubauer Family Assistant Professor in the Department of Computer Science at the University of Chicago in 2024.
Pei is interested in security, software engineering, and machine learning, with a focus on data-driven program analysis-related approaches to improve security and reliability of traditional and AI-based software systems. He develops machine learning models that can reason about program structure and behavior to precisely and efficiently analyze, detect, and fix software bugs and vulnerabilities.
Pei received his BA in Computer Science at Hong Kong Baptist University, his MS in Computer Science at Purdue University, and his PhD in Computer Science from Columbia University. During his PhD, he also worked at Google DeepMind and Microsoft Research, building robust and efficient machine learning models for code understanding and generation.